New AI technology delivers unprecedented on-device intelligence for IoT : Page 3 of 5

April 09, 2020 //By Thomas Ensergueix – Senior Director, Low Power IoT Business
Endpoint AI is accessible to many more with simplified software development on Arm
Arm has expanded its AI platform to bring the benefits of AI to billions enabling more distributed compute from the cloud and edge to endpoint devices, and providing new opportunities, such as more natural human interaction on smaller devices.

The first processor with Arm Helium vector extensions for improved performance and efficiency, the Cortex-M55, delivers up to 15x improvement in performance in machine learning applications and up to 5x improvement performance in digital signal processing (DSP) applications compared to previous Arm Cortex-M processors. Designers also enjoy increased creativity to differentiate within a coherent software development environment. In future, designers also will be able to leverage Arm Custom Instructions at the RTL level, coming in 2021, which provide the opportunity to extend the MCU’s capabilities for workload-specific optimization.

Based on a four-stage integer pipeline design, the Cortex-M55 processor is a fully synthesizable, mid-range processor that is designed for the microcontroller and deeply embedded system market. The processor offers high compute performance across both scalar and vector operations with low power consumption, fast interrupt handling, and enhanced system debug with extensive breakpoint and trace capabilities.  

The Ethos-U55 is the industry’s first licensable microNPU designed for microcontroller-class devices. To make designing with the Ethos-U55 more efficient, the device is integrated within a single Cortex-M toolchain, familiar to millions of developers, to provide exceptional performance improvement without additional software complexity. The open-source CMSIS-NN library to support machine learning and CMSIS-DSP are available to make the design experience even more efficient.

Ethos-U55, when combined with Cortex-M55, increases ML workload performance by up to 480x over existing Cortex-M based systems and can be as small as 0.1 mm2 in 16nm for AI applications in cost-sensitive and energy-constrained devices. It also offers an additional 32x ML performance boost over Cortex-M55 for more demanding ML systems. A single toolchain for Ethos-U55 and Cortex-M eases development and accelerates the creation of AI applications.

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